





import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class 			__UpperCamelCase    (							A__	, unittest.TestCase    ):
     __A	:  Optional[int]							  =   BarthezTokenizer
     __A	:  Union[str, Any]							  =   BarthezTokenizerFast
     __A	:  List[Any]							  =   True
     __A	:  str							  =   True





     def 		UpperCamelCase(     self					):
        super().setUp()

        _UpperCAmelCase           =   BarthezTokenizerFast.from_pretrained('''moussaKam/mbarthez'''					)
        tokenizer.save_pretrained(self.tmpdirname					)
        tokenizer.save_pretrained(self.tmpdirname				,							legacy_format=_UpperCamelCase					)
        _UpperCAmelCase           =   tokenizer





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   '''<pad>'''
        _UpperCAmelCase           =   1

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(_UpperCamelCase					)				,							_UpperCamelCase					)
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(_UpperCamelCase					)				,							_UpperCamelCase					)





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   list(self.get_tokenizer().get_vocab().keys()					)

        self.assertEqual(vocab_keys[0]				,							'''<s>'''					)
        self.assertEqual(vocab_keys[1]				,							'''<pad>'''					)
        self.assertEqual(vocab_keys[-1]				,							'''<mask>'''					)
        self.assertEqual(len(_UpperCamelCase					)				,							101122					)





     def 		UpperCamelCase(     self					):
        self.assertEqual(self.get_tokenizer().vocab_size				,							101122					)





     @require_torch
     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
        _UpperCAmelCase           =   [0, 57, 3018, 70307, 91, 2]

        _UpperCAmelCase           =   self.tokenizer(
            _UpperCamelCase				,							max_length=len(_UpperCamelCase					)				,							padding=_UpperCamelCase				,							truncation=_UpperCamelCase				,							return_tensors='''pt'''					)
        self.assertIsInstance(_UpperCamelCase				,							_UpperCamelCase					)

        self.assertEqual((2, 6)				,							batch.input_ids.shape					)
        self.assertEqual((2, 6)				,							batch.attention_mask.shape					)
        _UpperCAmelCase           =   batch.input_ids.tolist()[0]
        self.assertListEqual(_UpperCamelCase				,							_UpperCamelCase					)





     def 		UpperCamelCase(     self					):
        if not self.test_rust_tokenizer:
           return

        _UpperCAmelCase           =   self.get_tokenizer()
        _UpperCAmelCase           =   self.get_rust_tokenizer()

        _UpperCAmelCase           =   '''I was born in 92000, and this is falsé.'''

        _UpperCAmelCase           =   tokenizer.tokenize(_UpperCamelCase					)
        _UpperCAmelCase           =   rust_tokenizer.tokenize(_UpperCamelCase					)
        self.assertListEqual(_UpperCamelCase				,							_UpperCamelCase					)

        _UpperCAmelCase           =   tokenizer.encode(_UpperCamelCase				,							add_special_tokens=_UpperCamelCase					)
        _UpperCAmelCase           =   rust_tokenizer.encode(_UpperCamelCase				,							add_special_tokens=_UpperCamelCase					)
        self.assertListEqual(_UpperCamelCase				,							_UpperCamelCase					)

        _UpperCAmelCase           =   self.get_rust_tokenizer()
        _UpperCAmelCase           =   tokenizer.encode(_UpperCamelCase					)
        _UpperCAmelCase           =   rust_tokenizer.encode(_UpperCamelCase					)
        self.assertListEqual(_UpperCamelCase				,							_UpperCamelCase					)





     @slow
     def 		UpperCamelCase(     self					):
        # fmt: off
        _UpperCAmelCase           =   {'''input_ids''': [[0, 490, 14328, 4507, 354, 47, 43669, 95, 25, 78117, 20215, 19779, 190, 22, 400, 4, 35343, 80310, 603, 86, 24937, 105, 33438, 94762, 196, 39642, 7, 15, 15933, 173, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 10534, 87, 25, 66, 3358, 196, 55289, 8, 82961, 81, 2204, 75203, 7, 15, 763, 12956, 216, 178, 14328, 9595, 1377, 69693, 7, 448, 71021, 196, 18106, 1437, 13974, 108, 9083, 4, 49315, 7, 39, 86, 1326, 2793, 46333, 4, 448, 196, 74588, 7, 49315, 7, 39, 21, 822, 38470, 74, 21, 66723, 62480, 8, 22050, 5, 2]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
        # fmt: on

        # moussaKam/mbarthez is a french model. So we also use french texts.
        _UpperCAmelCase           =   [
            '''Le transformeur est un modèle d\'apprentissage profond introduit en 2017, '''
            '''utilisé principalement dans le domaine du traitement automatique des langues (TAL).''',
            '''À l\'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus '''
            '''pour gérer des données séquentielles, telles que le langage naturel, pour des tâches '''
            '''telles que la traduction et la synthèse de texte.''',
        ]

        self.tokenizer_integration_test_util(
            expected_encoding=_UpperCamelCase				,							model_name='''moussaKam/mbarthez'''				,							revision='''c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'''				,							sequences=_UpperCamelCase				,							)







"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


_SCREAMING_SNAKE_CASE   :							List[str]          =		{}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _SCREAMING_SNAKE_CASE   :							str          =		['''NllbTokenizer''']

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _SCREAMING_SNAKE_CASE   :							Optional[Any]          =		['''NllbTokenizerFast''']


if TYPE_CHECKING:
  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_nllb import NllbTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_nllb_fast import NllbTokenizerFast

else:
  import sys

  _SCREAMING_SNAKE_CASE   :							Any          =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




